Cognitive neuroscientists and clinicians seek insight into the distribution and temporal orchestration of human brain regions involved in cognitive processing. According to our general model and hypothesis, 'complex behavior is mapped at the level of multi-focal neural systems rather than specific anatomical sites, giving rise to brain-behavior relationships that are both localized and distributed' (Mesulam MM, Ann Neurol 28:597-613, 1990). Understanding how the human brain works requires knowledge of this functional neuroanatomy; namely, 'what' type of processing is performed, 'where' different processing areas are, 'when' temporal processing is organized between distributed areas, and 'how' large-scale distributed neuronal interactions underlying perception and cognition emerge. During the first 4 years of our funded research, we developed methodology combining functional MRI (fMRI) and magnetoencephalography / electroencephalography (MEG/EEG) data to obtain noninvasive spatiotemporal maps of cerebral activity with both high temporal (milliseconds) and spatial (millimeters) resolution, providing us with information about the 'what', 'where', and 'when'. This methodological development will be continued and extended in this grant application. [unreadable] [unreadable] Specifically, we will improve fMRI and MEG/EEG data acquisition and analysis methods, develop our finite element method to explicitly combine MEG and EEG data, and compare various inverse solution approaches, to increase the precision of the spatiotemporal brain imaging approach. Further, we will develop dynamic structural equation modeling approaches based on our integrated fMRI and MEG/EEG data, to allow us to study 'how' large-scale distributed neuronal interactions give rise to perception and cognition. Finally, we will apply these methodological advances in noninvasive studies of human visual system processing. Namely, we will study retinotopic organization, motion and complex stimuli processing, and the dynamic changes underlying plasticity and learning. Our work will provide a unique non-invasive methodology to map human brain function at a spatiotemporal resolution that has been previously attainable only in non-human animal models. Given the increasing availability of both MRI and EEG/MEG, our combined approach should have significant impact on human brain mapping in health and disease.